Seguint la distinció d'Edgar Morin entre "complexitat general" i "complexitat restringida", podem efectivament distingir entre dues aproximacions diferents al fenomen de la complexitat, que han donat lloc a dues escoles diferenciades i sovint fins i tot oposades. D'una banda, la "complexitat general" consistiria en una aproximació epistemològica a la complexitat, entesa com diria Henri Atlan com a "mesura de la ignorància" d'un subjecte observador respecte a un objecte observat caracteritzat per la seva "autopoiesi" i "clausura operacional" (Varela i Maturana). D'altra banda, la "complexitat restringida" consistiria en una aproximació metodològica mitjançant modelització computacional (com la simulació multi-agents) al comportament emergent i auto-organitzador dels sistemes complexos, que resultaria no determinista i sovint contraintuïtiu. Entre els referents de la primera escola es troben, entre d'altres, Edgar Morin, Ilya Prigogine, Francisco Varela o Heinz von Foerster. Entre els de la segona, Murray Gell-Mann, Robert Axelrod, John Holland o Stephen Wolfram. En la nostra presentació, proposem una confluència d'aquestes dues tendències des de la perspectiva d'una "sociologia complexa" possible que integraria els dos vessants en un paradigma comú unificat. D'una banda, presentarem, des d'una aproximació epistemològica de complexitat general, la naturalesa auto-organitzadora i morfogenètica del sistema social complex. De l'altra, presentarem des d'una aproximació metodològica de complexitat restringida, exemples de simulació multi-agents del comportament emergent i auto-organitzador del sistema social complex. Proposarem finalment un paradigma de sociologia complexa que integri les dues vies d'aproximació al fenomen de la complexitat.
Rodrigo Ledesma-Aguilar ( Northumbria University, Newcastle, United Kingdom)
In 1977, Picknett and Bexon published a seminal paper that has since shaped how we think about droplet evaporation on solid surfaces. In their article, they identified two extreme “modes” of evaporation on flat surfaces: on a perfectly smooth solid a droplet would evaporate keeping a constant shape, whilst on a perfectly rough surface the droplet edge would remain “pinned” to the solid, and thus the droplet would keep a constant footprint. Picknett and Bexon named these the “constant contact angle” and “constant contact area” modes of evaporation. In practice, it is often assumed that an evaporating droplet follows an alternation between these two limiting modes, in what is now termed the “stick-slip” mode of evaporation.
One of the defining features of stick-slip evaporation is the role of surface roughness. Roughness appears at small scales in the form of chemical or topographical defects which pin the edge of an evaporating droplet. A stick-slip sequence is then controlled by the energy-barriers that the droplet overcomes during de-pinning events, and which are predictable only in a few textbook cases. Therefore, and despite its apparent simplicity, droplet evaporation is a remarkably complicated process, which has proved notoriously difficult to predict and, crucially, control.
In this talk we challenge the widespread conception that pinning is the dominant mechanism controlling droplet evaporation, and put forward the idea of a snap mode of evaporation. Unlike stick-slip, snap evaporation occurs on smooth (pinning-free) surfaces that have a non-flat topography. In snap evaporation, the interaction of the surface of the droplet with the smooth solid topography determines, in a predictable way, the sequence of conformations that the droplet will take upon evaporation. Experimentally, we demonstrate this new evaporation mode using, as a model system, a water droplet evaporating on a wavy ultra-smooth lubricant-infused surface. Mathematically, we analyse our results using full hydrodynamics lattice-Boltzmann simulations which allow us to deduce that snap evaporation occurs as a sequence of well-defined quasi-equilibrium states interrupted by dynamic snap events. Our experiments and numerical simulations allow us to present a mathematical model based on bifurcation theory that further reveals the points where snap events are triggered, which obey a strict hierarchy dictated by the underlying surface topography.
Our main conclusion is that snap evaporation is governed by shape bifurcations controlled by the interaction between the surface of the droplet and the underlying smooth solid geometry, and not by the energy barriers imposed by pinning on a rough surface. Furthermore, our results imply that knowledge of the geometry of a pinning-free surface is sufficient to determine the sequence of conformations that a droplet will take upon evaporation on that surface. Therefore, snap evaporation is an amenable route to programmable surfaces for controlled evaporation in heat and mass transfer applications.
Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures and the comprehension of their dynamics is strategical for the understanding of neural processing. In this talk, I will clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of the neural activity, as expected, but it can also promote neural reactivation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition. However, the random pruning of the connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of the neurons. Thus the number of firing neurons reveals a minimum at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by the neurons with higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, the system passes from a perfectly regular evolution to an irregular bursting dynamics.
Daniel Rodríguez Amor (MIT)
Microbiomes are complex, dynamic communities intimately related to their environments. Despite the increasing efforts at developing a comprehensive ecological understanding of these microbial ecosystems, we are still far from a predictive theory to routinely engineer their community dynamics in order to promote health or fight environmental deterioration. Here, we study, both theoretically and experimentally, the dynamics between steady states of two different microbial ecosystems. The first model system permitted us to analyze how environmental resources shape the spatial dynamics of bacterial population fronts. Interestingly, we show that improved environments can slow down range expansions of mutualistic bacterial strains. In the second model, we explore transitions between population stable states induced by short-term perturbations. On the one hand, we show that environmental perturbations (such as antibiotic shocks) can induce shifts between stable states that can be predicted by analyzing the interactions between bacteria and their environment. On the other hand, we propose that transient invaders (alien species that interact with the community for shorts periods of time) can be a common cause of shifts between microbial stable states.